Toward Improved Environmental Stability of Polymer:Fullerene and Polymer:Nonfullerene Organic Solar Cells: A Common Energetic Origin of Light- and Oxygen-Induced Degradation

With the emergence of nonfullerene electron acceptors resulting in further breakthroughs in the performance of organic solar cells, there is now an urgent need to understand their degradation mechanisms in order to improve their intrinsic stability through better material design. In this study, we present quantitative evidence for a common root cause of light-induced degradation of polymer:nonfullerene and polymer:fullerene organic solar cells in air, namely, a fast photo-oxidation process of the photoactive materials mediated by the formation of superoxide radical ions, whose yield is found to be strongly controlled by the lowest unoccupied molecular orbital (LUMO) levels of the electron acceptors used. Our results elucidate the general relevance of this degradation mechanism to both polymer:fullerene and polymer:nonfullerene blends and highlight the necessity of designing electron acceptor materials with sufficient electron affinities to overcome this challenge, thereby paving the way toward achieving long-term solar cell stability with minimal device encapsulation

The Buffer Gas Beam: An Intense, Cold, and Slow Source for Atoms and Molecules

Beams of atoms and molecules are stalwart tools for spectroscopy and studies of collisional processes. The supersonic expansion technique can create cold beams of many species of atoms and molecules. However, the resulting beam is typically moving at a speed of 300-600 m/s in the lab frame, and for a large class of species has insufficient flux (i.e. brightness) for important applications. In contrast, buffer gas beams can be a superior method in many cases, producing cold and relatively slow molecules in the lab frame with high brightness and great versatility. There are basic differences between supersonic and buffer gas cooled beams regarding particular technological advantages and constraints. At present, it is clear that not all of the possible variations on the buffer gas method have been studied. In this review, we will present a survey of the current state of the art in buffer gas beams, and explore some of the possible future directions that these new methods might take

Assessment of QCM array schemes for mixture identification: Citrus scented odors

© 2016 The Royal Society of Chemistry. QCM sensor arrays are promising systems for volatile complex mixture analysis. Such mixtures, sometimes termed odors, can prove to be challenging targets for accurate identification using conventional approaches. As a result, development of novel gas sensing systems and materials for identification of complex mixtures has garnered much interest in recent years. Herein, we present a comparative study between traditional and alternative quartz crystal microbalance (QCM) array sensing schemes for complex mixture identification. In this study, several citrus scented odors were chosen for identification using three different QCM sensing scheme. A traditional multisensor array (MSA) scheme was compared to a recently introduced virtual sensor array (VSA) scheme and identification results were found to be comparable (84-91% to 73-98% accurate). In addition, a new sensing scheme developed by combining complementary MSA and VSA schemes is introduced. In this regard, a virtual multisensor array (V-MSA), with enhanced data density, allowed accurate identification (100%) of complex mixtures (odor samples) over multiple concentrations. While each method employed is promising, the newly presented V-MSA scheme is superior to each of the previously presented array sensing methods for complex mixture analysis. To the best of our knowledge, this is the first report of a QCM V-MSA

QCM virtual multisensor array for fuel discrimination and detection of gasoline adulteration

© 2017 Elsevier Ltd Herein, a simplistic quartz crystal microbalance (QCM) approach for discrimination of petroleum based fuels is presented. In this regard, a quartz crystal microbalance (QCM) virtual multisensor array (V-MSA) was employed to discriminate between different petroleum based fuels and to detect gasoline adulteration with high accuracy. First, an ionic liquid based V-MSA was used to discriminate between four fuel types (petroleum ether, gasoline, kerosene, and diesel). Subsequently, the system was used to successfully discriminate between three gasoline grades as a precursor for studies of gasoline adulteration. Finally, the system was used to detect and determine the nature of several gasoline adulterants at different v/v ratios (1%, 10%, 20% and 40%). Excellent accuracy (100%) was achieved for each study extolling the potential of this approach. This report represents the first example of a QCM sensor array utilized for detection of gasoline adulteration

QCM virtual sensor array: Vapor identification and molecular weight approximation

© 2017 Elsevier B.V. Herein, we present a promising approach for simultaneous identification and molecular weight approximation of closely related pure organic vapors using the quartz crystal microbalance (QCM). In this regard, a QCM virtual sensor array (VSA) was fabricated employing a binary blend of ionic liquid and polymer, i.e. 1-hexyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide ([HMIm][NTf2]) and poly(methyl methacrylate). This VSA technique allows discrimination/identification of closely related alcohols including isomers, while use of a composite coating facilitates molecular weight approximation of this set employing only the first harmonic. Statistical analyses (principal component and discriminant analyses) allowed identification of all analytes with extremely high accuracy. Molecular weight approximations were achieved with a linear correlation of R2≈0.99. This is the first report of a QCM sensor array that allows both identification and molecular weight approximation of organic vapors

Phthalocyanine- and porphyrin-based GUMBOS for rapid and sensitive detection of organic vapors

© 2014 Elsevier B.V. Metal complexes of porphyrins and phthalocyanines are attractive materials for designing recognition elements for chemical sensors, and hence they have been the focus of intense research. An interesting feature of these materials is that they can be functionalized at multiple positions to create sensors having slightly different selectivities. Considering the importance of these materials, herein, we report the synthesis and vapor-sensing characteristics of novel porphyrin- and phthalocyanine-based GUMBOS. More specifically, sodium counterions of copper (II) meso-tetra (4-carboxyphenyl) porphyrin (CuTCPP) and copper phthalocyanine-3,4,4″,4″-tetrasulfonic acid (CuPcS4) were replaced by trihexyl(tetradecyl)phosphonium cations to respectively produce the GUMBOS compounds, [P66614]4[CuTCPP] and [P66614]4[CuPcS4]. The resulting compounds were found to be solids with considerably lower melting points. These GUMBOS were then coated on the surface of a quartz crystal resonator, and the vapor sensing characteristics were evaluated by exposing the sensors to 11 different organic vapors. These materials exhibited excellent sensing characteristics; moreover, the two sensors exhibited cross-reactive response patterns, making these compounds very promising candidates for array-based vapor-sensing applications

Class specific discrimination of volatile organic compounds using a quartz crystal microbalance based multisensor array

© 2018 Elsevier B.V. The use of quartz crystal microbalance (QCM) sensor arrays for analyses of volatile organic compounds (VOC) has attracted significant interest in recent years. In this regard, a group of uniformed materials based on organic salts (GUMBOS) has proven to be promising recognition elements in QCM based sensor arrays due to diverse properties afforded by this class of tunable materials. Herein, we examine the application of four novel phthalocyanine based GUMBOS as recognition elements for VOC sensing using a QCM based multisensor array (MSA). These synthesized GUMBOS are composed of copper (II) phthalocyaninetetrasulfonate (CuPcS4) anions coupled with ammonium or phosphonium cations respectively (tetrabutylammonium (TBA), tetrabutylphosphonium (P4444), 3-(dodecyldimethyl-ammonio)propanesulfonate (DDMA), and tributyl-n-octylphosphonium (P4448)). These materials were characterized using ESI-MS and FTIR, while thermal properties were investigated using TGA. Vapor sensing properties of these GUMBOS towards a set of common VOCs at three sample flow rate ratios were examined. Upon exposure to VOCs, each sensor generated analyte specific response patterns that were recorded and analyzed using principal component and discriminant analyses. Use of this MSA allowed discrimination of analytes into different functional group classes (alcohols, chlorohydrocarbons, aromatic hydrocarbons, and hydrocarbons) with 98.6% accuracy. Evaluation of these results provides further insight into the use of phthalocyanine GUMBOS as recognition elements for QCM-based MSAs for VOC discrimination

Rational Design of QCM‑D Virtual Sensor Arrays Based on Film Thickness, Viscoelasticity, and Harmonics for Vapor Discrimination

Herein, we demonstrate an alternative strategy for creating QCM-based sensor arrays by use of a single sensor to provide multiple responses per analyte. The sensor, which simulates a virtual sensor array (VSA), was developed by depositing a thin film of ionic liquid, either 1-octyl-3-methylimidazolium bromide ([OMIm]­[Br]) or 1-octyl-3-methylimidazolium thiocyanate ([OMIm]­[SCN]), onto the surface of a QCM-D transducer. The sensor was exposed to 18 different organic vapors (alcohols, hydrocarbons, chlorohydrocarbons, nitriles) belonging to the same or different homologous series. The resulting frequency shifts (Δ<i>f</i>) were measured at multiple harmonics and evaluated using principal component analysis (PCA) and discriminant analysis (DA) which revealed that analytes can be classified with extremely high accuracy. In almost all cases, the accuracy for identification of a member of the same class, that is, intraclass discrimination, was 100% as determined by use of quadratic discriminant analysis (QDA). Impressively, some VSAs allowed classification of all 18 analytes tested with nearly 100% accuracy. Such results underscore the importance of utilizing lesser exploited properties that influence signal transduction. Overall, these results demonstrate excellent potential of the virtual sensor array strategy for detection and discrimination of vapor phase analytes utilizing the QCM. To the best of our knowledge, this is the first report on QCM VSAs, as well as an experimental sensor array, that is based primarily on viscoelasticity, film thickness, and harmonics

QCM virtual multisensor array for fuel discrimination and detection of gasoline adulteration

© 2017 Elsevier Ltd Herein, a simplistic quartz crystal microbalance (QCM) approach for discrimination of petroleum based fuels is presented. In this regard, a quartz crystal microbalance (QCM) virtual multisensor array (V-MSA) was employed to discriminate between different petroleum based fuels and to detect gasoline adulteration with high accuracy. First, an ionic liquid based V-MSA was used to discriminate between four fuel types (petroleum ether, gasoline, kerosene, and diesel). Subsequently, the system was used to successfully discriminate between three gasoline grades as a precursor for studies of gasoline adulteration. Finally, the system was used to detect and determine the nature of several gasoline adulterants at different v/v ratios (1%, 10%, 20% and 40%). Excellent accuracy (100%) was achieved for each study extolling the potential of this approach. This report represents the first example of a QCM sensor array utilized for detection of gasoline adulteration

Molecular weight sensing properties of ionic liquid-polymer composite films: Theory and experiment

Ionic liquids (ILs) are rapidly emerging as important coating materials for highly sensitive chemical sensing devices. In this regard, we have previously demonstrated that a quartz crystal microbalance (QCM) coated with a binary mixture of an IL and cellulose acetate can be employed for detection and molecular weight estimation of organic vapors (J. Mater. Chem. 2012, 22, 13732). Herein, we report follow-up studies aimed at formulating the theoretical basis for our previously observed relationship between molecular weight and changes in the QCM parameters. In the current work, we have investigated the vapor sensing characteristics of a series of binary blends of ILs and polymers over a wider concentration range of analytes, and a quadratic equation for estimating the approximate molecular weight of an organic vapor is proposed. Additionally, the frequency (f) and dissipation factor (D) at multiple harmonics were measured by use of a quartz crystal microbalance with dissipation monitoring (QCM-D). These QCM-D data were then analyzed by fitting to various models. It is observed that the behavior of these films can be best described by use of the Maxwell viscoelastic model. In light of these observations, a plausible explanation for the correlation between the molecular weight of absorbed vapors and the QCM parameters is presented. Our previous findings appear to be a special case of this more general observation. Overall, these results underscore the true potential of IL-based composite materials for discrimination and molecular weight estimation of a broad range of chemical vapors. This journal is © the Partner Organisations 2014